Deep Learning with Azure: Building and Deploying Artificial Intelligence Solutions on the Microsoft AI Platform

© Mathew Salvaris, Danielle Dean, Wee Hyong Tok 2018

Mathew Salvaris, Danielle Dean and Wee Hyong TokDeep Learning with Azurehttps://doi.org/10.1007/978-1-4842-3679-6_7

7. Recurrent Neural Networks

Mathew Salvaris¹ , Danielle Dean² and Wee Hyong Tok³

(1)

London, UK

(2)

Westford, Massachusetts, USA

(3)

Redmond, Washington, USA

 

The previous chapter showed how a deep learning model—specifically CNNs—could be applied to images. The process could be decoupled into a feature extractor that figures out the optimal hidden-state representation of the input (in this case a vector of feature maps) and a classifier (typically a fully connected layer). This chapter focuses on the hidden-state representation of other forms of data and explores RNNs. RNNs are especially ...